high performance computing on graphics processing units: hgpu.org

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An Introduction to High Performance Computing on AWS

David Pellerin, Dougal Ballantyne, Adam Boeglin

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Tags: Cloud, Cluster computing, Computer science, CUDA, OpenCL

August 13, 2015 by hgpu

Perception of Acoustical Spatial Attributes and Impression in Virtually Rendered Sound Field

Yukio Iwaya, Makoto Otani, Takao Tsuchiya, Yasushi Inoguchi

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Tags: Acoustics, Computer science, CUDA, GPU cluster, nVidia, OpenMPI, Tesla M2075

August 13, 2015 by hgpu

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration

Yunjin Chen, Thomas Pock

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Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 780 Ti, Package, Signal denoising

August 13, 2015 by hgpu

Accelerating IISPH: A Parallel GPGPU Solution Using CUDA

Andre Eliasson, Pontus Franzen

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Tags: Algorithms, CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce GTX 970, nVidia Quadro K4000, OpenMP, Thesis

August 12, 2015 by hgpu

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application

Blesson Varghese, Javier Prades, Carlos Reano, Federico Silla

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Tags: Computer science, CUDA, Finance, nVidia, Tesla K20, Virtualization

August 12, 2015 by hgpu

GPU Pro 6: Advanced Rendering Techniques

Wolfgang Engel (editor)

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Tags: 3D Graphics and Realism, Book, Computer science, CUDA, DirectCompute, DirectX, Games, nVidia, OpenCL, OpenGL, Rendering, Visualization

August 12, 2015 by hgpu

Performance analysis of parallel gravitational N-body codes on large GPU cluster

Siyi Huang, Rainer Spurzem, Peter Berczik

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Tags: Astrophysics, CUDA, GPU cluster, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Performance, Tesla M2050, Tesla M2070

August 12, 2015 by hgpu

Efficient Numerical Evaluation of Feynman Integral

Zhao Li, Jian Wang, Qi-Shu Yan, Xiaoran Zhao

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Tags: CUDA, High Energy Physics - Phenomenology, nVidia, Physics, QCD, Tesla K20

August 12, 2015 by hgpu

Optimizing strassen matrix multiply on GPUs

Ayaz ul Hasan Khan, Mayez Al-Mouhamed, Allam Fatayer

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Data parallelism, Matrix multiplication, nVidia, Tesla K20

August 11, 2015 by hgpu

A Parallel Implementation of the Self Organising Map using OpenCL

Gavin Davidson

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Tags: Algorithms, Computer science, Machine learning, nVidia, nVidia GeForce GTX 590, OpenCL, Package, Self-organizing map

August 11, 2015 by hgpu

Portable parallelized blowfish via RenderScript

Spencer Davis, Brandon Jones, Hai Jiang

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Tags: Algorithms, Android, Computer science, Java, RenderScript, Security

August 11, 2015 by hgpu

GPU-Disasm: A GPU-based x86 Disassembler

Evangelos Ladakis, Giorgos Vasiliadis, Michalis Polychronakis, Sotiris Ioannidis, Georgios Portokalidis

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 770, Security

August 11, 2015 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Perception of Acoustical Spatial Attributes and Impression in Virtually Rendered Sound Field

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration

Accelerating IISPH: A Parallel GPGPU Solution Using CUDA

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application

GPU Pro 6: Advanced Rendering Techniques

Performance analysis of parallel gravitational N-body codes on large GPU cluster

Efficient Numerical Evaluation of Feynman Integral

Optimizing strassen matrix multiply on GPUs

A Parallel Implementation of the Self Organising Map using OpenCL

Portable parallelized blowfish via RenderScript

GPU-Disasm: A GPU-based x86 Disassembler

Recent source codes

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Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

INT v.s. FP: A framework to compare low-bit integer and float-point formats

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NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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